Online Algorithm
A class of algorithms that process input arriving incrementally and must make decisions immediately without knowledge of future input. Their performance is measured by the competitive ratio.
Timeline (last 90 days)
The core of online algorithms lies in the "veil of uncertainty": we do not know what the input sequence will look like, but we hope to perform well no matter what the sequence is.
The competitive ratio is defined as the maximum, over worst-case input sequences, of the ratio of the online algorithm's cost to the optimal offline algorithm's cost.
The optimal strategy for the secretary problem is to wait through an observation period without deciding, then choose the first candidate better than everyone before.
Any online algorithm that strictly satisfies the budget must incur an entropy loss of Ω(R).
The online algorithm allows risk managers to update EVaR estimates in real time as new trades and new market quotes arrive, using a single pass over the data.
All Facts (5)
The core of online algorithms lies in the "veil of uncertainty": we do not know what the input sequence will look like, but we hope to perform well no matter what the sequence is.
50%UnverifiedThe competitive ratio is defined as the maximum, over worst-case input sequences, of the ratio of the online algorithm's cost to the optimal offline algorithm's cost.
50%UnverifiedThe optimal strategy for the secretary problem is to wait through an observation period without deciding, then choose the first candidate better than everyone before.
50%UnverifiedAny online algorithm that strictly satisfies the budget must incur an entropy loss of Ω(R).
50%UnverifiedThe online algorithm allows risk managers to update EVaR estimates in real time as new trades and new market quotes arrive, using a single pass over the data.
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